{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "46c04170-e87c-4bd3-8e42-7f147ab945cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "生成 erp_order 模拟数据行数：1133\n",
      "\n",
      "根据模拟数据汇总得到的月度销量：\n",
      "   月份  2021年  2022年\n",
      "0  1月   1686   1385\n",
      "1  2月   1345   1846\n",
      "2  3月   1934   1654\n",
      "3  4月   1658   1936\n",
      "4  5月   1865   2564\n",
      "5  6月   1936   2236\n",
      "\n",
      "校验通过：汇总结果与目标表完全一致！\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import random\n",
    "from datetime import datetime, timedelta\n",
    "import calendar\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from faker import Faker\n",
    "\n",
    "# ===================== 1. 配置与目标数据 =====================\n",
    "\n",
    "fake = Faker(\"zh_CN\")\n",
    "random.seed(42)\n",
    "np.random.seed(42)\n",
    "\n",
    "# 目标月度销量表（和截图完全一致）\n",
    "months = [\"1月\", \"2月\", \"3月\", \"4月\", \"5月\", \"6月\"]\n",
    "summary_target = pd.DataFrame({\n",
    "    \"月份\": months,\n",
    "    \"2021年\": [1686, 1345, 1934, 1658, 1865, 1936],\n",
    "    \"2022年\": [1385, 1846, 1654, 1936, 2564, 2236],\n",
    "})\n",
    "\n",
    "# 转成方便索引的 dict: {(year, month): target_qty}\n",
    "target_qty = {}\n",
    "for i, m in enumerate(range(1, 7)):\n",
    "    target_qty[(2021, m)] = summary_target.loc[i, \"2021年\"]\n",
    "    target_qty[(2022, m)] = summary_target.loc[i, \"2022年\"]\n",
    "\n",
    "\n",
    "# ===================== 2. 工具函数：某年某月随机时间 =====================\n",
    "\n",
    "def random_datetime_in_month(year: int, month: int) -> datetime:\n",
    "    \"\"\"生成指定年、月内的随机 datetime（避免 Faker 版本差异问题）\"\"\"\n",
    "    first_day = datetime(year, month, 1, 0, 0, 0)\n",
    "    last_day = calendar.monthrange(year, month)[1]\n",
    "    last_dt = datetime(year, month, last_day, 23, 59, 59)\n",
    "    delta_seconds = int((last_dt - first_day).total_seconds())\n",
    "    offset = random.randint(0, delta_seconds)\n",
    "    return first_day + timedelta(seconds=offset)\n",
    "\n",
    "\n",
    "# ===================== 3. 生成 erp_order 模拟数据（>=1000 条） =====================\n",
    "\n",
    "rows = []\n",
    "order_id = 1\n",
    "\n",
    "stores = [\"天猫旗舰店\", \"京东自营店\", \"微信小程序\", \"抖音旗舰店\"]\n",
    "platforms = [\"天猫\", \"京东\", \"微信小程序\", \"抖音\"]\n",
    "status_choices = [\"待发货\", \"已发货\", \"已完成\"]\n",
    "refund_status_choices = [\"未申请退款\", \"成功退款\", \"退款关闭\"]\n",
    "colors = [\"黑色\", \"白色\", \"蓝色\", \"灰色\", \"卡其色\"]\n",
    "sizes = [\"S\", \"M\", \"L\", \"XL\", \"XXL\"]\n",
    "provinces = [\"北京\", \"上海\", \"广东\", \"浙江\", \"江苏\", \"四川\", \"湖北\", \"山东\"]\n",
    "\n",
    "for year in (2021, 2022):\n",
    "    for month in range(1, 7):\n",
    "        total_q = target_qty[(year, month)]\n",
    "\n",
    "        # 每月生成 80~120 笔订单，整体总数在 1000+ 以上\n",
    "        n_orders = random.randint(80, 120)\n",
    "        n_orders = min(n_orders, total_q)\n",
    "\n",
    "        # 用 Dirichlet 生成占比，再映射为整数数量，保证 sum == total_q 且每笔 >= 1\n",
    "        if n_orders == 1:\n",
    "            quantities = np.array([total_q])\n",
    "        else:\n",
    "            weights = np.random.dirichlet(np.ones(n_orders))\n",
    "            base = np.floor(weights * (total_q - n_orders)).astype(int) + 1\n",
    "            diff = total_q - base.sum()\n",
    "            base[0] += diff\n",
    "            quantities = base\n",
    "\n",
    "        assert quantities.sum() == total_q\n",
    "\n",
    "        for q in quantities:\n",
    "            order_time = random_datetime_in_month(year, month)\n",
    "            payment_date = order_time + timedelta(hours=random.randint(0, 72))\n",
    "            shipping_date = payment_date + timedelta(days=random.randint(0, 7))\n",
    "\n",
    "            quantity = int(q)\n",
    "            unit_price = round(random.uniform(80, 600), 2)\n",
    "            product_amount = round(unit_price * quantity, 2)\n",
    "\n",
    "            shipping_fee = random.choice([0, 0, 0, 8, 12])\n",
    "            payable_amount = round(product_amount + shipping_fee, 2)\n",
    "\n",
    "            discount = round(random.uniform(0, 0.2) * payable_amount, 2)\n",
    "            paid_amount = round(payable_amount - discount, 2)\n",
    "\n",
    "            spu = f\"SPU{random.randint(1000, 9999)}\"\n",
    "            sku_suffix = random.choice(colors) + random.choice(sizes)\n",
    "            sku = f\"{spu}-{sku_suffix}\"\n",
    "\n",
    "            row = {\n",
    "                \"id\": order_id,\n",
    "                \"internal_order_number\": f\"IN{year}{month:02d}{order_id:06d}\",\n",
    "                \"online_order_number\": f\"ON{year}{month:02d}{order_id:06d}\",\n",
    "                \"store_name\": random.choice(stores),\n",
    "                \"full_channel_user_id\": fake.uuid4().replace(\"-\", \"\")[:32],\n",
    "                \"shipping_date\": shipping_date,\n",
    "                \"payment_date\": payment_date,\n",
    "                \"payable_amount\": payable_amount,\n",
    "                \"paid_amount\": paid_amount,\n",
    "                \"status\": random.choice(status_choices),\n",
    "                \"consignee\": fake.name(),\n",
    "                \"spu\": spu,\n",
    "                \"order_time\": order_time,\n",
    "                \"province\": random.choice(provinces),\n",
    "                \"city\": fake.city_name(),\n",
    "                \"platform\": random.choice(platforms),\n",
    "                \"sub_order_number\": f\"SUB{year}{month:02d}{order_id:06d}\",\n",
    "                \"online_sub_order_number\": f\"SUBON{year}{month:02d}{order_id:06d}\",\n",
    "                \"original_online_order_number\": f\"ORION{year}{month:02d}{order_id:06d}\",\n",
    "                \"sku\": sku,\n",
    "                \"quantity\": quantity,\n",
    "                \"unit_price\": unit_price,\n",
    "                \"product_name\": fake.word() + \"时尚单品\",\n",
    "                \"color_and_spec\": f\"{random.choice(colors)} {random.choice(sizes)}\",\n",
    "                \"product_amount\": product_amount,\n",
    "                \"original_price\": round(unit_price * random.uniform(1.1, 1.5), 2),\n",
    "                \"is_gift\": random.choice([\"否\", \"否\", \"否\", \"是\"]),\n",
    "                \"sub_order_status\": random.choice(status_choices),\n",
    "                \"refund_status\": random.choice(refund_status_choices),\n",
    "                \"registered_quantity\": quantity,\n",
    "                \"actual_refund_quantity\": 0 if random.random() > 0.9 else random.randint(0, quantity),\n",
    "            }\n",
    "\n",
    "            rows.append(row)\n",
    "            order_id += 1\n",
    "\n",
    "df_erp = pd.DataFrame(rows)\n",
    "print(f\"生成 erp_order 模拟数据行数：{len(df_erp)}\")  # 应该 >= 1000\n",
    "\n",
    "# ===================== 4. 按月汇总销量，并校验与目标表一致 =====================\n",
    "\n",
    "df_erp[\"year\"] = df_erp[\"order_time\"].dt.year\n",
    "df_erp[\"month\"] = df_erp[\"order_time\"].dt.month\n",
    "\n",
    "agg = (\n",
    "    df_erp\n",
    "    .groupby([\"year\", \"month\"])[\"quantity\"]\n",
    "    .sum()\n",
    "    .unstack(\"year\")\n",
    "    .loc[range(1, 7), [2021, 2022]]\n",
    "    .reset_index()\n",
    ")\n",
    "agg.rename(columns={\"month\": \"月份\", 2021: \"2021年\", 2022: \"2022年\"}, inplace=True)\n",
    "\n",
    "# 关键修正：去掉列索引的 name，避免与 summary_target 不一致\n",
    "agg.columns.name = None\n",
    "\n",
    "agg[\"月份\"] = agg[\"月份\"].astype(str) + \"月\"\n",
    "\n",
    "print(\"\\n根据模拟数据汇总得到的月度销量：\")\n",
    "print(agg)\n",
    "\n",
    "pd.testing.assert_frame_equal(\n",
    "    agg.reset_index(drop=True),\n",
    "    summary_target.reset_index(drop=True)\n",
    ")\n",
    "print(\"\\n校验通过：汇总结果与目标表完全一致！\")\n",
    "\n",
    "# ===================== 5. 画图：复刻 Excel 深色双折线图 =====================\n",
    "\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "fig.patch.set_facecolor(\"#101a3c\")\n",
    "ax.set_facecolor(\"#101a3c\")\n",
    "\n",
    "x = range(1, 7)\n",
    "y_2021 = summary_target[\"2021年\"].values\n",
    "y_2022 = summary_target[\"2022年\"].values\n",
    "\n",
    "line1, = ax.plot(x, y_2021, marker=\"o\", linewidth=2.5, color=\"#ff6b81\", label=\"2021年\")\n",
    "line2, = ax.plot(x, y_2022, marker=\"o\", linewidth=2.5, color=\"#3da5ff\", label=\"2022年\")\n",
    "\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels(months, color=\"white\", fontsize=11)\n",
    "\n",
    "ax.set_ylim(0, 3200)\n",
    "ax.set_yticks(range(0, 3201, 500))\n",
    "ax.set_yticklabels([str(v) for v in range(0, 3201, 500)], color=\"white\", fontsize=10)\n",
    "\n",
    "ax.grid(axis=\"y\", linestyle=\"--\", linewidth=0.8, color=\"#3b476a\", alpha=0.8)\n",
    "ax.tick_params(axis=\"x\", colors=\"white\")\n",
    "ax.tick_params(axis=\"y\", colors=\"white\")\n",
    "\n",
    "fig.suptitle(\n",
    "    \"2022年上半年各月同比去年销量\",\n",
    "    fontsize=22,\n",
    "    color=\"white\",\n",
    "    x=0.5,\n",
    "    y=0.95,\n",
    "    fontweight=\"bold\"\n",
    ")\n",
    "\n",
    "ax.set_title(\n",
    "    \"上半年同比去年增长明显，5月份同比增长最多，增长近40%\",\n",
    "    fontsize=13,\n",
    "    color=\"white\",\n",
    "    pad=20\n",
    ")\n",
    "\n",
    "for xx, v in zip(x, y_2021):\n",
    "    ax.text(xx, v + 40, str(v), ha=\"center\", va=\"bottom\",\n",
    "            color=\"#ff6b81\", fontsize=10)\n",
    "\n",
    "for xx, v in zip(x, y_2022):\n",
    "    ax.text(xx, v + 40, str(v), ha=\"center\", va=\"bottom\",\n",
    "            color=\"#3da5ff\", fontsize=10)\n",
    "\n",
    "legend = ax.legend(loc=\"upper right\", fontsize=11)\n",
    "for text in legend.get_texts():\n",
    "    text.set_color(\"white\")\n",
    "\n",
    "for spine in [\"top\", \"right\"]:\n",
    "    ax.spines[spine].set_visible(False)\n",
    "for spine in [\"left\", \"bottom\"]:\n",
    "    ax.spines[spine].set_color(\"#5c6480\")\n",
    "\n",
    "fig.text(\n",
    "    0.01, 0.02,\n",
    "    \"*注：数据来源于公司销售系统，统计日期截至2022.06.30\",\n",
    "    fontsize=9,\n",
    "    color=\"white\"\n",
    ")\n",
    "\n",
    "plt.tight_layout(rect=[0, 0.05, 1, 0.9])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26f4618d-fb85-4eed-bcd5-fbbac9c09fd8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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